Ontology based relevance criteria for semantic web search engine

End users get large information through the web. The search engine which allows increasing the information retrieval accuracy exploited a key content of semantic web resources of concepts and relations. Tremendous information gets poured in to the web pages for every query raised by the end user. Most of the pages are query related and fulfill the intention of the end users. There are some pages with useless information also. The web architecture represented by the semantic web provides the layered architecture which possibly overcomes this limitation. Search engines which usually allow increasing the information retrieval accuracy by exploiting a key content of semantic web resources, that is the relations that are existing in the query. There is a huge repository which makes very difficult for the end users to explore to have an easy catch up of the required concept many modifications are being done. This paper we deal with the page rank algorithm to be used in conjunction with the semantic web search engines that usually extracted from the user queries and on annotated resources. Page Relevance Score is measured as the probability that a retrieved resource actually contains those relations existence was assumed by the user at the time of query definition.